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AIA
2007
15 years 4 months ago
A framework for generating data to simulate changing environments
A fundamental assumption often made in supervised classification is that the problem is static, i.e. the description of the classes does not change with time. However many practi...
Anand M. Narasimhamurthy, Ludmila I. Kuncheva
ML
2002
ACM
220views Machine Learning» more  ML 2002»
15 years 2 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
MLDM
2009
Springer
15 years 9 months ago
PMCRI: A Parallel Modular Classification Rule Induction Framework
In a world where massive amounts of data are recorded on a large scale we need data mining technologies to gain knowledge from the data in a reasonable time. The Top Down Induction...
Frederic T. Stahl, Max A. Bramer, Mo Adda
GIS
1992
ACM
15 years 7 months ago
Machine Induction of Geospatial Knowledge
Machine learning techniques such as tree induction have become accepted tools for developing generalisations of large data sets, typically for use with production rule systems in p...
Peter A. Whigham, Robert I. McKay, J. R. Davis
NIPS
1994
15 years 4 months ago
From Data Distributions to Regularization in Invariant Learning
Ideally pattern recognition machines provide constant output when the inputs are transformed under a group G of desired invariances. These invariances can be achieved by enhancing...
Todd K. Leen